Most complex brain network studies on the AD-related alterations have been largely based on characteristic path length (i.e., the shortest paths) and its derivatives (e.g., assortativity and resilience) ([1]}, [2]}, [3]}, [4]}, [5]}). For example, the averaged characteristic path length of all pairs of brain regions characterizes network’s global efficiency, while the shortest path-based local connectedness defines local clustering coefficients or local efficiency. Recent studies also broadly defines small-worldness, an important brain network property balancing local integration and global reachability ([6]}).
AD has been usually associated with disconnected or less efficient connectome with suboptimal organization ([7]}, [8]}, [9]}, [10]}). MCI, on the other hand, usually manifests increasing FC and suboptimal small-worldness ([11]}, [12]}, [13]}), possibly due to a compensatory effect for maintaining normative cognition. While these studies jointly indicated that cost efficiency can be a good property of the brain network where brain regions are optimally connected to work efficiently together, this phenomenon can be also prominent when only network’s backbone (e.g., the top 5% strongest connections) considered ([14]}, [15]}). The brain network’s topology can manifest different properties when viewed with more redundant (but weaker) links, which could be equally important as the efficiency-based metrics in understanding the neural mechanisms of diseases ([16]}, [17]}, [18]}).
